Experiments in applying advanced data mining and integration to hydro-meteorological scenarios

We present the results of applying advanced data integration and data mining (DMI) technology, developed in the FP7 project ADMIRE, to a set of hydro-meteorological pilot scenarios. The DMI technology includes a data processing architecture and its implementation by a set of tools, and a new DMI process definition language called DISPEL. It is based on the popular OGSA-DAI framework. The pilot scenarios were defined by hydrological and meteorological experts and their aim is to try predict hydro-meteorological processes in cases, where standard physical models for the chosen geographical domain are not present, or give unsatisfactory results. The obtained results show that the application of ADMIRE DMI technology is beneficient to the domain experts.

[1]  Ivan Janciak,et al.  Advanced Data Mining and Integration Research for Europe , 2009 .

[2]  Frank Leymann,et al.  Modeling Stateful Resources with Web Services , 2004 .

[3]  Martin Seleng,et al.  Mining environmental data in hydrological scenarios , 2010, 2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery.

[4]  Norman W. Paton,et al.  The design and implementation of Grid database services in OGSA‐DAI , 2005, Concurr. Pract. Exp..

[5]  Mike Jackson,et al.  Introduction to OGSA-DAI Services , 2004, SAG.

[6]  Marek Ciglan,et al.  Hydro-meteorological Scenarios Using Advanced Data Mining and Integration , 2009, 2009 Sixth International Conference on Fuzzy Systems and Knowledge Discovery.